Abstract
Deoxyribonucleic acid (DNA) sequencing is an important task in computational biology. In recent years the specific problem of DNA sequencing by hybridization has attracted quite a lot of interest in the optimization community. This led to the development of several metaheuristic approaches such as tabu search and evolutionary algorithms. In this work we propose an ant colony algorithm to resolve this problem. In addition, we apply our algorithm within a multi-level framework which helps in significantly reducing the computation time. The results show that our algorithm is currently among the state-of-the-art methods for this problem.
This work was supported by the Spanish CICYT project OPLINK (grant TIN-2005-08818-C04-01), and by the “Juan de la Cierva” program of the Spanish Ministry of Science and Technology of which Christian Blum is a post-doctoral research fellow.
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Blum, C., Vallès, M.Y. (2006). Multi-level Ant Colony Optimization for DNA Sequencing by Hybridization. In: Almeida, F., et al. Hybrid Metaheuristics. HM 2006. Lecture Notes in Computer Science, vol 4030. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11890584_8
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DOI: https://doi.org/10.1007/11890584_8
Publisher Name: Springer, Berlin, Heidelberg
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